This is a simple package to create a lionplot. A lionplot is a categorical scatterplot with errorbars. Consider that you have three categories (independent variables), e.g., "orange", "blue" and "green", and two groups, "A" and "B", and a dependent variable, e.g., "y". You can use this plot to compare the means of the dependent variable between the two groups, for each category.
Assume you have the following arrays
print(x)
>> ['blue', 'green', 'orange', 'blue', 'green', 'orange']
print(y)
>> [11.00385443, 9.48885355, 9.34449002, 16.19138262, 16.06753942, 16.89107449]
print(yerr)
>> [0.9982947 , 1.0022813 , 0.99986582, 0.99908995, 0.99837166, 0.99931396]
print(group)
>> ['A', 'A', 'A', 'B', 'B', 'B']where x is the category, y is the average, yerr is the confidence interval (95%) and group is the group assignment. You can create a lionplot as follows:
from lionplot import lionplot
lionplot(
x=x,
y=y,
ax=ax,
yerr=yerr,
hue_values=group,
)@2025, Leonardo Alchieri